Statistical shape models are powerful tools for image interpretation and shape analysis. A simple, yet effective, way of building such models is to capture the statistics of sampled point coordinates over a training set of example shapes. However, a major drawback of this approach is the need to establish a correspondence across the training set. In 2-D, a correspondence is often defined using a s...
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A vital task in the planning of peripheral bronchoscopy is the segmentation of the airway tree from a 3-D multidetector computed tomography chest scan. Unfortunately, existing methods typically do not sufficiently extract the necessary peripheral airways needed to plan a procedure. We present a robust method that draws upon both local and global information. The method begins with a conservative s...
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The aim of this paper is to introduce a variational image segmentation method for assessing the aberrant crypt foci (ACF) in the human colon captured in vivo by endoscopy. ACF are thought to be precursors for colorectal cancer, and therefore their early detection may play an important clinical role. We enhance the active contours without edges model of Chan and Vese to account for the ACF's...
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A methodology for estimating the spatial distribution of elastic moduli using the steady-state dynamic response of solids immersed in fluids is presented. The technique relies on the ensuing acoustic field from a remotely excited solid to inversely estimate the spatial distribution of Young's modulus of biological structures (e.g., breast tissue). This work proposes the use of Gaussian radial basi...
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Evaluating rupture risk of abdominal aortic aneurysms is critically important in reducing related mortality without unnecessarily increasing the rate of elective repair. According to the current clinical practice aneurysm rupture risk is (mainly) estimated from its maximum diameter and/or expansion rate; an approach motivated from statistics but known to fail often in individuals. In contrast, rec...
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Magnetic resonance imaging (MRI) on patients with implanted deep brain stimulators (DBSs) can be hazardous because of the antenna-effect of leads exposed to the incident radio-frequency field. This study evaluated electromagnetic field and specific absorption rate (SAR) changes as a function of lead resistivity on an anatomically precise head model in a 3T system. The anatomical accuracy of our he...
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Diffusion tensor imaging (DTI) provides important information on the structure of white matter fiber bundles as well as detailed tissue properties along these fiber bundles in vivo. This paper presents a functional regression framework, called FRATS, for the analysis of multiple diffusion properties along fiber bundle as functions in an infinite dimensional space and their association with ...
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We advocate a task-based approach to the assessment of image quality using the Bayesian ideal observer. The Bayesian ideal observer provides an absolute upper bound for performance estimates. However, using the full images as inputs to the observer is often infeasible due to their high dimensionality. A practical alternative is to reduce the dimensionality of the images by applying channels, while...
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Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In Makni et aL, 2005 and Makni et aL, 2008, a detection-estimation framework has been proposed to tackle these problems jointly, since they are connected to one another. In the Bayesian formalism, detection is achieved by modeli...
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Reconstruction algorithms for fluorescence tomography have to address two crucial issues: 1) the ill-posedness of the reconstruction problem, 2) the large scale of numerical problems arising from imaging of 3-D samples. Our contribution is the design and implementation of a reconstruction algorithm that incorporates general Lp regularization (p ¿¿ 1). The originality of this work lie...
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In this response letter, technical issues raised by the comments concerning determination of arterial input function, cardiac and respiratory related motion artifacts, contrast agent application, and compartmental model fitting in our work are addressed in detail, and a discussion on identifying causes of uncertainty in physiological measurement and how to minimize their contribution is presented.
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Aims & Scope

IEEE Transactions on Medical Imaging (T-MI) encourages the submission of manuscripts on imaging of body structure, morphology and function, including cell and molecular imaging and all forms of microscopy. The journal publishes original contributions on medical imaging achieved by modalities including ultrasound, x-rays, magnetic resonance, radionuclides, microwaves, and optical methods. Contributions describing novel acquisition techniques, medical image processing and analysis, visualization and performance, pattern recognition, machine learning, and related methods are encouraged. Studies involving highly technical perspectives are most welcome.
The focus of the journal is on unifying the sciences of medicine, biology, and imaging. It emphasizes the common ground where instrumentation, hardware, software, mathematics, physics, biology, and medicine interact through new analysis methods. Strong application papers that describe novel methods are particularly encouraged. Papers describing important applications based on medically adopted and/or established methods without significant innovation in methodology will be directed to other journals.
To qualify for publication, submitted manuscripts must be previously unpublished and must not be under consideration elsewhere. The Editor-in-Chief and an Associate Editor will perform a quick review of each manuscript to evaluate the manuscript in terms of novelty, quality and appropriateness and may return the manuscript immediately if it does not meet minimum standards of quality, originality, and scope. Manuscripts will ONLY be accepted in electronic format through ScholarOne Manuscripts. Please go to the ScholarOne Manuscripts website at http://mc.manuscriptcentral.com/tmi-ieee or to the TMI website http://www.ieee-tmi.org/ to find instructions to electronically submit your manuscript. Do not send original submissions or revisions directly to the Editor-in-Chief or Associate Editors.